[英]Aggregate Function to dataframe while retaining rows in Pandas
I want to aggregate my data based off a field known as COLLISION_ID
and a count of each COLLISION_ID
.我想根据一个名为
COLLISION_ID
的字段和每个COLLISION_ID
的计数来聚合我的数据。
I want to remove repeating COLLISION_IDs since they have the same Coordinates, but retain a count of occurrences in original data-set.我想删除重复的 COLLISION_ID,因为它们具有相同的坐标,但保留原始数据集中的出现次数。
My code is below我的代码如下
df2 = df1.groupby(['COLLISION_ID'])[['COLLISION_ID']].count()
I would like my data returned as the COLLISION_ID
numbers, the count, and the remaining columns of my data which are not shown here(~40 additional columns that will be filtered later)我希望我的数据以
COLLISION_ID
数字、计数和我的数据的剩余列的形式返回,这些列未在此处显示(大约 40 列稍后将被过滤)
If you are talking about filter, we should do transform
如果您在谈论过滤器,我们应该进行
transform
df1['count_col']=df1.groupby(['COLLISION_ID'])['COLLISION_ID'].transform('count')
Then you can filter the df1 with column count然后您可以使用列数过滤 df1
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